Automatic selection of candidate investments for transmission expansion planning

Abstract

This paper deals explicitly with the problem of proposing candidate lines (sometimes referred to as technical alternatives) for Transmission Expansion Planning (TEP). Candidate lines have been traditionally regarded as expert-provided system information. However, given the need to plan larger networks, identifying interesting candidates is an issue of increasing relevance and complexity. This paper proposes a consistent method to tackle this problem. First, an automatic and objective candidate discovery mechanism based on sensitivities proposes potentially interesting investments. Then, a candidate management strategy filters the list of candidates to keep problem size within tractable levels in a Mathematical Programming context without compromising global optimality. Finally, a candidate analysis tool reveals the relationships among investments from a relatively fast and simple power flow study. This information can be interesting to provide support for expansion decisions. These theoretical developments are complemented by a realistic case study which illustrates the applicability of the method.

This paper deals explicitly with the problem of proposing candidate lines (sometimes referred to as technical alternatives) for Transmission Expansion Planning (TEP). Candidate lines have been traditionally regarded as expert-provided system information. However, given the need to plan larger networks, identifying interesting candidates is an issue of increasing relevance and complexity. This paper proposes a consistent method to tackle this problem. First, an automatic and objective candidate discovery mechanism based on sensitivities proposes potentially interesting investments. Then, a candidate management strategy filters the list of candidates to keep problem size within tractable levels in a Mathematical Programming context without compromising global optimality. Finally, a candidate analysis tool reveals the relationships among investments from a relatively fast and simple power flow study. This information can be interesting to provide support for expansion decisions. These theoretical developments are complemented by a realistic case study which illustrates the applicability of the method.